{"id":"W2082090599","doi":"10.1260/0957-4565.41.10.29","title":"A New Method of Nonlinear Feature Extraction for Multi-Fault Diagnosis of Rotor Systems","year":2010,"lang":"en","type":"article","venue":"Noise & Vibration Worldwide","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Feature extraction; Rotor (electric); Fault (geology); Pattern recognition (psychology); Nonlinear system; Nonlinear dimensionality reduction; Artificial intelligence; Feature (linguistics); Computer science; Feature vector; Control theory (sociology); Engineering; Dimensionality reduction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003254085,0.000219087,0.0003785528,0.0002505097,0.00003677675,0.00003570359,0.0001928544,0.0002292522,0.00008017139],"category_scores_gemma":[0.0003437697,0.0002192892,0.0001551132,0.0002921163,0.00001631099,0.0003305824,0.00001882748,0.0002996713,0.000004150151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000350895,"about_ca_system_score_gemma":0.00004394446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000253495,"about_ca_topic_score_gemma":0.0004764626,"domain_scores_codex":[0.9988246,0.00004379816,0.0005043671,0.0002239681,0.000217799,0.0001854853],"domain_scores_gemma":[0.9987063,0.000403802,0.0002228659,0.0003795558,0.0001864197,0.0001010206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000595366,0.0002174437,0.006297773,0.0007964102,0.00009916813,0.000001154466,0.0002838918,0.01308509,0.8994393,0.0009317149,0.04070852,0.03807998],"study_design_scores_gemma":[0.0004961384,0.00005154485,0.002929894,0.0001097575,0.00005357901,0.000003319649,0.00001415362,0.3170826,0.6529825,0.00003641891,0.02605601,0.0001840675],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03728536,0.0002403895,0.9581391,0.000275545,0.0009925859,0.001973913,0.0001729416,0.0005401091,0.0003801077],"genre_scores_gemma":[0.2049673,0.000052575,0.7933668,0.00002998561,0.0003567707,0.0008133592,0.00008327873,0.00007090205,0.0002590362],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3039975,"threshold_uncertainty_score":0.8942354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533827201563125,"score_gpt":0.3337773644672433,"score_spread":0.318439092451612,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}